commit b644e681ff78cb297e95b218f8df932c9b9ada19
parent e9f16fea049298daccc047abd241ac3f02a2a487
Author: Vincent EYMET <vincent.eymet@meso-star.com>
Date: Wed, 7 Jul 2021 14:22:54 +0200
Rewrite the htrdr overview in the README file
Diffstat:
| M | README.md | | | 76 | ++++++++++++++++++++++++++++++++++++++++++++-------------------------------- |
1 file changed, 44 insertions(+), 32 deletions(-)
diff --git a/README.md b/README.md
@@ -1,35 +1,47 @@
-# High-Tune: RenDeRer
-
-This program is a part of the [High-Tune](http://www.umr-cnrm.fr/high-tune/)
-project: it illustrates the implementation of efficient radiative transfer
-Monte-Carlo algorithms in cloudy atmospheres.
-
-htrdr is an image renderer in the visible part of the spectrum, for scenes
-composed of an atmospheric gas mixture, clouds, and a ground. It uses spectral
-data that should be provided for the pressure and temperature atmospheric
-vertical profile defined along the Z axis, the liquid water content in
-suspension within the clouds that is a result of Large Eddy Simulation
-computations, and the optical properties of water droplets that have been
-obtained from a Mie code. The user also has to provide: the characteristics of
-the simulated camera, the sensor definition, and the position of the sun. It is
-also possible to provide a geometry representing the ground. Both, the clouds
-and the ground, can be infinitely repeated along the X and Y axis.
-
-htrdr evaluates the intensity incoming on each pixel of the sensor array. The
-underlying algorithm is based on a Monte-Carlo method: it consists in
-simulating a given number of optical paths originating from the camera,
-directed into the atmosphere, taking into account light absorption and
-scattering phenomena. The computation is performed over the whole visible part
-of the spectrum, for the three components of the CIE 1931 XYZ colorimetric
-space that are subsequently recombined in order to obtain the final color for
-each pixel, and finally the whole image of the scene as seen from the required
-observation position.
-
-In addition of shared memory parallelism, htrdr supports the [*M*essage
-*P*assing *I*nterface](https://www.mpi-forum.org/) specification to
-parallelise its computations in a distribute memory environment; the htrdr
-binary can be run either directly or through a MPI process launcher like
-`mpirun`.
+# `htrdr`
+
+`htrdr` evaluates the intensity at any position (probe) of the scene, in any
+direction, in the presence of surfaces and an absorbing and diffusing
+semi-transparent medium, both for radiation sources that are internal to the
+medium (longwave) or external to the medium (shortwave). The intensity is
+calculated using the *Monte-Carlo* method: a number of optical paths are
+simulated backward, from the probe position and into the medium. Various
+algorithms are used, depending on the specificities of the nature and shape of
+the radiation source.
+
+Applications are theoretically possible to any configuration. However, it all
+eventually comes down to the possibility of using the physical data of
+interest, in their most common formats, in each scientific community. `htrdr`
+is currently suitable for two main application fields:
+
+1. *Atmospheric radiative transfer*: the clear-sky atmosphere is vertically
+ stratified, cloud thermodynamic data is provided on a regular 3D rectangular
+ grid, and surface optical properties can be provided for an arbitrary number
+ of materials. Internal radiation and solar radiation are taken into account.
+
+2. *Combustion* processes: thermodynamic data is provided at the nodes of an
+ unstructured tetrahedral mesh, while surface properties can still be
+ provided for various materials. The radiation source is only external: a
+ monochromatic laser sheet illuminates the inside of the combustion chamber
+ for diagnostic purposes.
+
+Since any observable radiative transfer is expressed as an integral of the
+intensity, and since there is a strict equivalence between the integral to be
+solved and the underlying Monte-Carlo algorithm (each integral results in the
+sampling of a random variable), the algorithms that calculate the radiance are
+used for computing various quantities:
+
+- *Images* on a camera sensor, in a given field of view. For combustion
+ applications, only monochromatic images are supported. In atmospheres, both
+ visible and infrared images are possible: CIE colorimetry is used for visible
+ images, while an infrared image is in fact a temperature map of luminosity,
+ over the required spectral interval.
+
+- *Flux density maps*, on a grid of sensors, integrated over an entire
+ hemisphere. In the case of combustion chambers, only monochromatic flux maps
+ can be calculated, while spectrally integrated flux density maps (both on the
+ visible part of the spectrum and on the infrared) are possible for
+ atmospheric applications.
## How to build
